Data Analytics Consultant

Key Responsibilities:

1.    Data Analysis and Reporting:

-        Gather, clean, and analyze data to support business operations and decision-making.

-        Design, develop, and maintain custom reports and dashboards using tools like Power BI, Qlik, or similar.

-        Ensure data integrity and accuracy in all reports by validating data sources and performing thorough checks.

2.    Data Extraction and Transformation:

-        Perform data transformation and cleaning using Python for deeper analysis and reporting.

-        Automate the extraction, transformation, and loading (ETL) of data using Python scripts or any advanced automation tools to streamline processes.

3. .    Artificial Intelligence (AI) Application:

-        Apply AI techniques to various business use cases to drive greater efficiency and innovation.

-        Develop, implement, and maintain AI models and solutions tailored to business needs, such as process optimization, predictive analytics, or automation.

-        Collaborate with cross-functional teams to identify opportunities where AI can add value and streamline operations.

4.    Business Intelligence & Insights:

-        Work with business stakeholders to define key performance indicators (KPIs) and metrics for reporting.

-        Develop and provide ad-hoc reports to various departments based on business needs.

-        Create and deliver insights through data visualization to help teams understand trends and patterns.

5.    Collaboration and Communication:

-        Partner with internal teams to understand their reporting and data analysis requirements.

-        Translate complex data sets into clear, understandable reports for non-technical stakeholders.

-        Communicate insights and findings effectively, providing recommendations to enhance business outcomes.

6.    Process Improvement:

-        Identify opportunities to optimize reporting processes through automation and improved data management practices.

-        Collaborate with IT and data engineering teams to enhance data architecture for better reporting and analytics.

Qualifications: 

1.    Technical Skills:

a.     Data Analysis: Proficiency in data analysis using Python (Pandas, NumPy) and data extraction and manipulation.

b.     Reporting Tools: Experience with reporting and business intelligence tools like Power BI, Qlik, or similar.

c.     ETL: Familiarity with ETL processes to automate data integration tasks.

d.     Data Visualization: Strong skills in creating visual representations of data for stakeholders.

e.     Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for data handling.

f.      AI & Machine Learning: Experience with AI and machine learning concepts, including implementing predictive analytics or leveraging AI-powered tools for enhanced data insights.

2.    Experience:

-        8+ years of experience in data analysis and reporting roles.

-        Proven ability to automate reporting processes using Python and SQL.

-        Experience working with large data sets and providing meaningful insights from complex data.

-        Demonstrated success in delivering accurate, actionable reports to business stakeholders.

-        AI: Demonstrated ability to apply AI techniques for data analysis, such as developing predictive models, automating data classification, or enhancing reporting with AI-driven insights.

3.    Soft Skills:

-        Strong analytical and problem-solving abilities.

-        Excellent proficiency in using Microsoft Office Applications (i.e. Excel, Words, PowerPoint, Outlook etc.).

-        Excellent communication skills, with the ability to explain complex data in simple terms.

-        Attention to detail and a commitment to delivering high-quality work.

-        Ability to work collaboratively across teams and manage multiple projects.

4.    Preferred Skills:

-        Experience with version control systems (e.g., Git).

-        Knowledge of statistical analysis and machine learning models.

-        Knowledge on Vehicle System

-        Familiarity with data governance and best practices for data security.

Qualifications

Graduate/ Post Graduate in Computer Science/ Information Science / Electronics or equivalent